Adaptive two time-scale receding horizon optimal control for greenhouse lettuce cultivation

Xu, Dan; Du, Sichun; Willigenburg, L.G. van

doi:10.1016/j.compag.2018.02.001

Cited by 43 publications

(17 citation statements)

References 18 publications

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“…Under a perfectly predicted greenhouse environment, the maximum yield can be calculated for any given energy use for the supplementary lighting. However, the problem (equations (18) and (19)) to be solved in the perfect solution is time consuming on the computer, and is not suitable for scenarios that require high real-time performance, especially if updated weather forecasts produce dynamic corrections. In this study, an optimisation method suitable for solving complex problems was proposed, that has two main features: 1) Instead of repeatedly solving the problem of maximum production and minimum energy consumption conflicts, a multiobjective minimisation method was developed, such as…”

Section: Optimisationmentioning

confidence: 99%

“…Xu et al . 19 developed a two time-scale receding horizon optimal control system to reduce energy consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Mahdavian and Wattanapongsakorn 18 take into account the dynamic electricity price, combined with the yield model, using genetic algorithms to optimise the amount of light energy at different times of the day. Xu et al 19 developed a two time-scale receding horizon optimal control system to reduce energy consumption.…”

Section: Introductionmentioning

confidence: 99%

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Optimal greenhouse lighting scheduling using canopy light distribution model: A simulation study on tomatoes

Wei

2019

Lighting Research & Technology

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Light is considered the most important environmental factor for greenhouse crops, and lack of lighting limits the productivity of greenhouses. Many studies have focused on improving the energy efficiency of lighting in agriculture. In this study, LED lights were mounted in the top, middle and bottom of the plant canopy to provide additional photosynthetically active radiation. Assuming that 100% of the predicted outdoor radiation is available, the canopy light distribution model was used to determine the relationship between the light energy consumption and the optimal yield. Decision-making on lighting scheduling may be considered as a constrained optimisation, and the status of the LEDs in a period acts as the decision variable. Besides, there are two objective functions: one is the energy consumed by the LED device; the other is the expected yield calculated by the crop model of tomatoes. The optimal solution of the multi-objective optimisation is not unique but corresponds to an infinite number of yield/energy combinations. Farmers can select these combinations according to additional restrictions such as energy efficiency ratio or photoperiod. The yield of our strategy was increased by 12.3% under the constraint of equal energy consumption compared to the greenhouse threshold control strategy. Given the same output as the constraint, the energy consumption was reduced by 30.1%.

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Section: Optimisationmentioning

confidence: 99%

“…Xu et al . 19 developed a two time-scale receding horizon optimal control system to reduce energy consumption.…”

Section: Introductionmentioning

confidence: 99%

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Optimal greenhouse lighting scheduling using canopy light distribution model: A simulation study on tomatoes

Wei

2019

Lighting Research & Technology

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“…Yao et al (2019) proposed a two-time scale control scheme for tracking and vibration suppression in cooperative manipulation by a team of space robots. Xu et al (2018) presented an adaptive two time-scale optimal controller which included on-line parameter estimation to control the effects of time-varying parameters. Owing to the hybrid nature of hub-beam systems, time-scale separation and two-time scale controller design seem to be promising for these systems; in some previous studies, the ideas have been investigated.…”

Section: Introductionmentioning

confidence: 99%

Cross term constructed Lyapunov function based two-time scale controller design and vibration suppression for a rotating hub-beam system

Khajepour

Vatankhah

Eghtesad

et al. 2019

Transactions of the Institute of Measurement and Control

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In this article, modeling and control of a rotating hub-beam system are studied. The system consists of a solid rotating cylinder and an attached flexible arm with a payload at the end. The rotation is supposed to be in the presence of gravity and the flexible arm is assumed to be a Euler-Bernoulli beam. To derive the equations of motion of the system, Lagrange’s method is applied. Moreover, Galerkin’s technique is employed to discretize the equations of motion. Furthermore, designing an appropriate two-time (slow and fast) scale controller in the presence of uncertainties is considered in order to track the desired hub angular position and suppress vibrations of the arm simultaneously. For the so-called slow subsystem, a novel controller design is proposed as two different cases, with and without the presence of uncertainties in system dynamics are considered; and accordingly, a control law for tracking the desired path is introduced based on the idea of using the cross-term constructed Lyapunov function. For the fast subsystem, a pole placement technique is used to suppress vibration of the beam. The simulation results indicate notable effectiveness of the proposed controller.

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“…The same was true for 4 out of 9 cases of model reuse. Cases of model reuse or extension by authors unrelated to the original publication are limited to quite simple models, as can be seen by their decomposition in Table 2.3: Xu et al (2018a) reused the model of Van Henten (2003), Mohamed & Hameed (2018) reused the model of Albright et al (2001), Gharghory (2020) and Subin et al (2020) reused the model of Pasgianos et al (2003), andJomaa et al (2019) reused the model of Blasco et al (2007), while using parameters from a previous study. Model extension without shared coauthors is also reserved for relatively simple models, e.g.…”

Section: Inheritance Of Process-based Greenhouse Climate Modelsmentioning

confidence: 99%

Energy saving by LED lighting in greenhouses : A process-based modelling approach

Katzin¹

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Chapter 2 investigates the discipline of process-based greenhouse modelling. The chapter shows that a considerable number of greenhouse models are being published, and sets out to understand the reasons for the existence of this multitude of models. In Section 2.2, substantial background on the concept of process-based greenhouse modelling is provided, and a general structure of these models is proposed. Subsequently, modelling studies published between 2018 and 2020 are analyzed according to this general structure. The studies are categorized according to their objectives, types of greenhouse they describe, and equipment they consider, and a model inheritance chart is presented, showing how current models are based on earlier works. Moreover, a comparison of modelling validation studies is performed. Based on this analysis, possible reasons for the abundance of greenhouse models are suggested, including a lack of model transparency and code availability, and a belief that model development is in itself a valuable research goal. The chapter ends with several recommendations for the future advancement of the discipline. These include promoting model transparency and availability of source code, and establishing shared datasets and evaluation benchmarks.Chapter 3 presents GreenLight, a process-based model for a greenhouse with a tomato crop, which describes the influence of HPS lamps and LEDs on the climate, crop, and energy use. In this chapter, GreenLight's performance is evaluated by comparing model predictions against data from two greenhouse compartments, one with HPS lamps and one with LEDs. The model is found to have a relative error in predictions of climate and energy use in the range of 1-12%. In order to promote transparency, the model is offered in an open source format at https://github.com/davkat1/GreenLight. In this way, the model is made available for inspection and extension by others.Chapter 4 uses GreenLight to predict the influence of replacing HPS lamps by LEDs in a greenhouse. A wide range of scenarios is considered, including varying climates, from subtropical China to arctic Sweden, and multiple settings for indoor temperature, lamp intensity, lighting duration, and insulation. In all scenarios, LEDs are found to reduce the energy demand for lighting by 40%, but to increase the demand for heating. This results in the total energy saving by transition to LEDs to be in the range of 10-25% for the majority of scenarios considered. An important factor influencing how much energy can be saved by a transition to LEDs is found to be the ratio between the lighting and heating demand of the greenhouse before the transition. Summary xiiiChapter 5 presents a novel concept for greenhouse climate control: heating a greenhouse by light. Considering the observation that all lamps provide heat as well as light, this chapter suggests that illuminating at high light intensities could eliminate the need to heat the greenhouse by the heating system. This approach could potentially be very efficient, as it utili...

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Adaptive two time-scale receding horizon optimal control for greenhouse lettuce cultivation

Cited by 43 publications

References 18 publications

Optimal greenhouse lighting scheduling using canopy light distribution model: A simulation study on tomatoes

Optimal greenhouse lighting scheduling using canopy light distribution model: A simulation study on tomatoes

Cross term constructed Lyapunov function based two-time scale controller design and vibration suppression for a rotating hub-beam system

Energy saving by LED lighting in greenhouses : A process-based modelling approach

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